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The same six features as the GFF3 file expressed in BED's 0-based half-open coordinates, where the start is one lower and the end is unchanged. Confusing the two conventions shifts every interval by a base, and this pair makes that shift a visible diff.
Benzene written in the V3000 extended format, where the legacy counts line reports zero atoms and the real counts live in an M V30 COUNTS record. A parser that trusts the old counts line reads an empty molecule and reports no error whatsoever.
Eight arithmetic expressions where binary floating point and exact decimal disagree, with both answers and the signed error side by side. Adding one cent a hundred times does not give one, and this file says by exactly how much.
Five calibration points with the nominal value, the measured value, the signed error and the expanded uncertainty at k=2 with its confidence level stated. It is a synthetic illustration of the layout, not an accredited certificate, and nothing in it refers to a real instrument or laboratory.
Five computations done twice, once with the obvious formula and once with the numerically stable one, with the relative error of the naive version alongside. The one-pass variance row is the memorable one: five values a millisecond apart near 1e8 can produce a negative variance.
Nine laboratory results where only four are plain numbers: two are below the detection limit, one is above range, two are missing in different spellings, and one is a legitimate small negative near the blank. Coercing the censored strings to numbers or to NaN both bias the summary, and the file distinguishes every case explicitly.
One row per molecule used across the chemistry fixtures, with formula, molecular weight, SMILES and the atom and bond counts each file should yield. It is the oracle a cheminformatics toolkit can be scored against without needing a second toolkit to generate the answers.
A CIF built entirely out of the constructs that break naive parsers: quoted values containing apostrophes and hashes, a semicolon-delimited multi-line text field, the distinct '?' and '.' markers, a standard uncertainty written as 1.2345(7), and a loop whose rows wrap across lines. Every one of them is legal CIF.
CSV reference listing the four expected HDF5 datasets with shapes and units for lightweight converter assertions. Stable P8 artifact p8-convert-hdf5-summary-csv.
Valid HDF5 hierarchy source with raw, processed, and metadata groups plus four unit-tagged datasets for Convert v2. Stable P8 artifact p8-convert-hdf5-source.
Every element of the synthetic phantom dataset as tag, value representation, meaning and encoded length, in the ascending tag order the standard mandates. Diff a parser's element list against it to check both the ordering rule and the two different length encodings.
A DICOM Part 10 file built byte by byte: 128-byte preamble, the DICM magic, an explicit-VR file meta group and a 27-element dataset ending in 16-bit pixel data. Every identifier is invented: the patient name is SYNTHETIC^PHANTOM, the instance UIDs sit under the unregistered 2.25 UUID arc, and the pixels are a generated pattern. There is no protected health information here and nothing in the file refers to a real person, device or study.
The same synthetic phantom written with the implicit-VR transfer syntax, where element types never appear on the wire and a reader must consult a data dictionary to know that Rows is a 16-bit integer. The file meta group stays explicit VR, which is the mixed-mode detail parsers most often miss. Every identifier is invented: the patient name is SYNTHETIC^PHANTOM, the instance UIDs sit under the unregistered 2.25 UUID arc, and the pixels are a generated pattern. There is no protected health information here and nothing in the file refers to a real person, device or study.
The identical element stream with the 128-byte preamble and the DICM magic stripped, which is how DICOM often arrives out of a network transfer or a database blob column. It is not a conformant Part 10 file and its content is entirely recoverable, so a reader should fall back rather than reject.
Ethanol as a V2000 molfile with fixed-column 3D coordinates, a nine-atom counts line and an eight-bond block. The column widths are part of the format rather than a convention, so it is a genuine test of fixed-width parsing rather than of whitespace splitting.
An SDfile wrapping the identical ethanol molfile plus five tagged data fields and the mandatory $$$$ terminator. The property block syntax — a header line, a value and a blank line — is where SDfile parsers usually diverge from molfile parsers.
Ethanol as a single tab-delimited SMILES record, the most compressed member of this family: three heavy atoms with every hydrogen implicit and no geometry whatsoever. Round-tripping molfile to SMILES and back is the classic lossy conversion, and this pair is the reference for it.
The same ethanol geometry in XYZ format: an atom count, a free-text comment line and one line of element and coordinates per atom. XYZ carries no connectivity at all, so converting to it from the molfile is a lossy operation that this pair makes measurable.
Five concatenated XYZ frames of the same ethanol molecule rotated rigidly about z in 15-degree steps, which keeps every interatomic distance constant. Frames are separated only by the next atom-count line, so a reader that expects a blank-line delimiter stops after frame one.
The same four contigs written one sequence per line rather than wrapped, which is how many pipelines emit FASTA and how many line-oriented parsers assume it always looks. Comparing against the wrapped twin proves a parser joins continuation lines instead of taking the first one.
Four 600-base synthetic contigs wrapped at the conventional 60 columns, with the length and an invented organism name in each header. The sequences come from a fixed seed, so they are reproducible and belong to nothing that exists.
Every twelfth base of the six reads with its Phred score, the ASCII character it takes under both offsets, and the error probability that score implies. It converts a quality-encoding argument into a lookup you can diff.
Six 60-base reads with Phred+33 quality strings, the modern Sanger encoding used by everything since Illumina 1.8. Quality declines along each read the way real sequencing does, so a mis-decoded offset produces implausible scores rather than plausible ones.
The identical reads and identical quality scores written with the legacy Phred+64 offset used by older Illumina pipelines. Decode it with the modern offset and every base looks 31 points better than it is, which is a silent quality inflation rather than a parse failure.
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